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Journal of Applied Remote Sensing

Using the enhanced vegetation index for deriving risk maps of desert locust (Schistocerca gregaria, Forskal) breeding areas in Egypt
Author(s): Osama Rabie Mahmoud Moustafa; Keith Cressman
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Paper Abstract

This study utilizes moderate resolution imaging spectroradiometer-enhanced vegetation index (EVI) imagery for deriving risk maps of desert locust breeding areas and proposes a simple EVI reclassification scheme that can be easily interpreted and used by field teams in Egypt during regular surveys. The proposed scheme was based on analysis of EVI imagery and locust survey data collected in southeast Egypt during a locust outbreak in 2011. It was found that areas with an EVI value of <0.05 were less likely to have locust breeding, areas with a value between 0.05 and 0.1 contained large-sized infestations with low to medium densities of locusts, and areas with EVI<0.1 hosted large-sized infestations with medium to high densities. The accuracy of the proposed reclassification was evaluated in the field during the winter breeding season of 2013, which coincided with another locust outbreak. The results suggest that the risk maps derived from reclassified EVI imagery represent a potentially useful tool for survey teams to use on a regular basis to better guide them to potential locust breeding sites. This could lead to surveys that are more efficient and effective in monitoring desert locust infestations in Egypt.

Paper Details

Date Published: 24 November 2015
PDF: 14 pages
J. Appl. Rem. Sens. 8(1) 084897 doi: 10.1117/1.JRS.8.084897
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Osama Rabie Mahmoud Moustafa, Ministry of Agriculture & Land Reclamation (Egypt)
Keith Cressman, Food and Agriculture Organization of the United Nations (Italy)

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